In cellular systems of today, the user performance can be improved by interference cancellation. Interference cancellation implies that the self-interference or interference from other users are removed or suppressed from the received signal. Multi-path propagation and transmission from different antennas make the signals not orthogonal in the receiver. The non-orthogonal signals will interfere with each other. However, by estimating all signals or a subset of the signals and removing those from the received signal, reduction in the desired signal interference can be achieved. This procedure can be done iteratively for increased performance.
Typically what is done is that the transmitted signal symbols and the channel coefficients for each user are estimated. The channel coefficients consist of the parameters determining the amplitudes, phases, and delays of the received multi-path signal components of a user signal. The transmitted signal is then regenerated and filtered through the estimated channel using the estimated channel coefficients, the channel estimates, to recreate a replica of the received signal for each user. Then for each desired signal, these replicas of the interfering signals can be subtracted, and the interference can be reduced.
Crucial for the cancellation performance is that the channel estimates of each multi-path are of enough high quality. Even though the transmitted signal symbols are estimated correctly, the channel estimation will always be subjected to interference and thermal noise. Especially when low data rate user signals are cancelled from the received signal, the system performance improvement can be considered low. This is because low data rate user signal likely have lower order modulation, where the requirement for the channel estimate qualities are lower than the requirement of higher order modulation for proper demodulation of the transmitted data. Hence, the channel estimate quality may be sufficiently good for demodulation, but may be less good for interference reconstruction.
There are proposals to improve the quality of the estimated channel coefficients by re-estimating them after each interference cancellation iteration. The channel estimates will then also be subjected to interference cancellation and can be used again in the following interference cancellation iteration to improve the interference cancellation performance.
No matter how much the channel estimates are improved, there will always be a question of whether the channel estimate qualities are good enough. Therefore, a method to determine channel estimate qualities for interference cancellation is desired.